Front cover image for Advanced methods of marketing research

Advanced methods of marketing research

Advanced Methods of Marketing Research has been specially compiled for students on advanced marketing research courses at the graduate and postgraduate levels, and on executive programs. This important text provides the first collection of the most sophisticated research techniques found in the discipline. It contains summaries of cutting-edge methods and original ideas certain to shape research in the years ahead. The contributors focus on the history of the methods, descriptions of their assumptions and content, and examples. Each chapter is self-contained and is prepared by one or more internationally renowned scholars. Questions and exercises are included to test and extend the reader's knowledge and provide hands-on experience. Seasoned researchers will find Advanced Methods of Marketing Research an essential update of their knowledge of classical procedures
Print Book, English, 1994
Blackwell Business, Cambridge, Mass., 1994
Aufsatzsammlung
xvii, 407 pages : illustrations ; 25 cm
9781557865496, 1557865493
29182369
Introduction / Richard P. Bagozzi
1. Advanced Topics in Structural Equation Models / Richard P. Bagozzi and Youjae Yi
2. Partial Least Squares / Claes Fornell and Jaesung Cha
3. Multivariate Statistical Models for Categorical Data / Jay Magidson
4. CHAID Approach to Segmentation Modeling: CHi-squared Automatic Interaction Detection / Jay Magidson
5. Cluster Analysis in Marketing Research / Phipps Arabie and Lawrence Hubert
6. Latent Class Multidimensional Scaling: A Review of Recent Developments in the Marketing and Psychometric Literature / Wayne S. DeSarbo, Ajay K. Manrai and Lalita A. Manrai
7. Conjoint Analysis / Jordan J. Louviere
8. Multiple Correspondence Analysis / Donna L. Hoffman, Jan de Leeuw and Ramesh V. Arjunji
9. Latent Structure and Other Mixture Models in Marketing: An Integrative Survey and Overview / William R. Dillon and Ajith Kumar
10. Review of Recent Developments in Latent Class Regression Models / Michel Wedel and Wayne S. DeSarbo